Apparatus and method for estimating bio-information

ABSTRACT

Example embodiments relate to an apparatus for non-invasively estimating bio-information is provided. An apparatus for estimating bio-information may include a sensor part including a pixel array of pixels, each pixel having a light source and a detector; and a processor configured to, based on an object being in contact with the sensor part, drive the sensor part based on a first sensor configuration; obtain contact information of the object based on an amount of light received by each pixel according to the first sensor configuration; determine a second sensor configuration based on the contact information; drive the sensor part based on the second sensor configuration; and estimate the bio-information based on light signals obtained according to the second sensor configuration.

CROSS-REFERENCE TO RELATED APPLICATION(S)

This application claims priority to Korean Patent Application No.10-2020-0111847, filed on Sep. 2, 2020, in the Korean IntellectualProperty Office, the entire disclosure of which is incorporated hereinby reference for all purposes.

BACKGROUND 1. Field

Example embodiments of the present disclosure relate to an apparatus andmethod for non-invasively estimating bio-information.

2. Description of Related Art

According to a general method of non-invasively measuring triglycerides,triglyceride concentrations in blood are estimated by placing ameasuring device, having a light source and an optical sensor, on bloodvessels and by measuring signals of scattered light passing throughblood. A change in blood triglyceride concentration leads to a change inscattering coefficient, such that the change in the scatteringcoefficient may be obtained from a change in the scattered lightsignals, and the blood triglyceride concentration may be estimated basedon the change in the scattering coefficient.

SUMMARY

According to an aspect of an example embodiment, an apparatus forestimating bio-information may include a sensor part including a pixelarray of pixels, each pixel having a light source and a detector; and aprocessor configured to, based on an object being in contact with thesensor part, drive the sensor part based on a first sensorconfiguration; obtain contact information of the object based on anamount of light received by each pixel according to the first sensorconfiguration; determine a second sensor configuration based on thecontact information; drive the sensor part based on the second sensorconfiguration; and estimate the bio-information based on light signalsobtained according to the second sensor configuration.

The first sensor configuration may include at least one of atime-division driving method, a sequential driving method, asimultaneous driving method, a driving order, a light source intensity,and a duration.

The processor may obtain the contact information based on at least oneof a pixel having an amount of light being greater than or equal to apredetermined threshold value, a pixel having an amount of light beinggreater than or equal to a predetermined percentage of an average valueof a total amount of light, a pixel having an amount of light beinggreater than or equal to a predetermined percentage of a maximum amountof light, and a pixel having an amount of light being greater than orequal to a predetermined percentage of an average value of an amount oflight falling within a predetermined range of the maximum amount oflight.

The processor may obtain the contact information including at least oneof a contact area of the object, a center point of the contact area, afingerprint center point, and a contact direction.

The processor may, based on the contact information, determine a lightsource pixel and a detector pixel of the second sensor configuration.

The processor may determine one or more pixels, located at predeterminedpositions in the contact direction, to be light source pixels of thesecond sensor configuration, among pixels in the contact area; anddetermine one or more pixels, located within a predetermined range fromthe center point of the contact area or the fingerprint center point, tobe detector pixels of the second sensor configuration.

The processor may map a reference area, a reference direction, and areference center point of a pre-defined reference sensor configurationto the contact area, the contact direction, and the center point of thecontact area; and based on the mapping, determine pixels correspondingto light source pixels of the pre-defined reference sensor configurationto be the light source pixels of the second sensor configuration, andpixels corresponding to detector pixels of the pre-defined referencesensor configuration to be detector pixels of the second sensorconfiguration.

The sensor part may obtain a fingerprint image based on the object beingin contact with the sensor part, and the processor may obtain thecontact information based on the fingerprint image.

The processor may, in response to the fingerprint center point not beinglocated within a predetermined range of the sensor part, control anoutput interface to guide a user to place the object on the sensor part.

The processor may calculate a scattering coefficient based on the lightsignals obtained according to the second sensor configuration; andestimate the bio-information based on the scattering coefficient.

The processor may, in response to the light signals being obtainedaccording to the second sensor configuration, calculate a similaritybetween the light signals; and select light signals, having thesimilarity being greater than or equal to a first threshold value, aslight signals for estimating the bio-information.

The processor may, in response to the light signals being obtainedaccording to the second sensor configuration, calculate a similaritybetween the light signals; and exclude light signals, having thesimilarity being less than or equal to a second threshold value, aslight signals for estimating the bio-information.

The bio-information may include at least one of triglyceride, body fatpercentage, body water, blood glucose, cholesterol, carotenoid, protein,and uric acid.

According to an aspect of an example embodiment, a method of estimatingbio-information may include, based on an object being in contact with asensor part, driving the sensor part based on a first sensorconfiguration; obtaining contact information of the object based on anamount of light received by each pixel of the sensor part according tothe first sensor configuration; determining a second sensorconfiguration based on the contact information; driving the sensor partbased on the second sensor configuration; and estimating thebio-information based on light signals obtained according to the secondsensor configuration.

The obtaining the contact information may include obtaining the contactinformation based on at least one of a pixel having an amount of lightbeing greater than or equal to a predetermined threshold value, a pixelhaving an amount of light being greater than or equal to a predeterminedpercentage of an average value of a total amount of light, a pixelhaving an amount of light being greater than or equal to a predeterminedpercentage of a maximum amount of light, and a pixel having an amount oflight being greater than or equal to a predetermined percentage of anaverage value of an amount of light falling within a predetermined rangeof the maximum amount of light.

The obtaining the contact information may include obtaining the contactinformation including at least one of a contact area of the object, acenter point of the contact area, a fingerprint center point, and acontact direction.

The determining the second sensor configuration may include determiningone or more pixels, located at predetermined positions in the contactdirection, to be light source pixels of the second sensor configuration,among pixels in the contact area; and determining one or more pixels,located within a predetermined range from the center point of thecontact area or the fingerprint center point, to be detector pixels ofthe second sensor configuration.

The determining the second sensor configuration may include mapping areference area, a reference direction, and a reference center point of apre-defined reference sensor configuration to the contact area, thecontact direction, and the center point of the contact area; and basedon the mapping, determining pixels corresponding to light source pixelsof the pre-defined reference sensor configuration to be the light sourcepixels of the second sensor configuration, and pixels corresponding todetector pixels of the pre-defined reference sensor configuration to bethe detector pixels of the second sensor configuration.

The method may include obtaining a fingerprint image based on the objectbeing in contact with the sensor part.

The obtaining the contact information may include obtaining the contactinformation based on the fingerprint image.

The method may include, in response to the fingerprint center point notbeing located within a predetermined range of the sensor part,controlling an output interface to guide a user to place the object onthe sensor part.

The estimating the bio-information may include calculating a scatteringcoefficient based on two or more light signals obtained by the sensorpart; and estimating the bio-information based on the scatteringcoefficient.

The estimating the bio-information may include, in response to the lightsignals being obtained by the sensor part, calculating a similaritybetween the light signals; and selecting light signals, having thesimilarity being greater than or equal to a first threshold value, aslight signals for estimating the bio-information.

The estimating of the bio-information may include, in response to thelight signals being obtained by the sensor part, calculating asimilarity between the light signals; and excluding light signals,having the similarity being less than or equal to a second thresholdvalue, as light signals for estimating the bio-information.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other aspects, features, and advantages of certain exampleembodiments of the present disclosure will be more apparent from thefollowing description taken in conjunction with the accompanyingdrawings, in which:

FIG. 1 is a block diagram illustrating an apparatus for estimatingbio-information according to an example embodiment;

FIG. 2 is a block diagram illustrating an apparatus for estimatingbio-information according to another example embodiment;

FIG. 3 is a block diagram illustrating a configuration of a processoraccording to an example embodiment;

FIGS. 4A and 4B are diagrams explaining an example of obtaining contactinformation of an object;

FIGS. 4C, 4D, and 4E are diagrams explaining an example of obtaining asecond sensor configuration;

FIGS. 5A and 5B are diagrams explaining an example of estimatingbio-information;

FIG. 6 is a flowchart illustrating a method of estimatingbio-information according to an example embodiment;

FIG. 7 is a diagram illustrating an example of a wearable device; and

FIG. 8 is a diagram illustrating an example of a smart device.

DETAILED DESCRIPTION

Details of example embodiments are provided in the following detaileddescription and drawings. Advantages and features of the presentdisclosure, and methods of achieving the same will be more clearlyunderstood from the following example embodiments described in detailwith reference to the accompanying drawings. Throughout the drawings andthe detailed description, unless otherwise described, the same drawingreference numerals will be understood to refer to the same elements,features, and structures.

It will be understood that although the terms “first,” “second,” etc.may be used herein to describe various elements, these elements shouldnot be limited by these terms. These terms are only used to distinguishone element from another. Also, the singular forms of terms are intendedto include the plural forms of the terms as well, unless the contextclearly indicates otherwise. It will be further understood that when anelement is referred to as “comprising” another element, the element isintended not to exclude one or more other elements, but to furtherinclude one or more other elements, unless explicitly described to thecontrary. In the following description, terms such as “unit” and“module” indicate a unit for processing at least one function oroperation and they may be implemented by using hardware, software, or acombination thereof. As used herein, expressions such as “at least oneof,” when preceding a list of elements, modify the entire list ofelements and do not modify the individual elements of the list. Forexample, the expression, “at least one of a, b, and c,” should beunderstood as including only a, only b, only c, both a and b, both a andc, both b and c, or all of a, b, and c.

Hereinafter, example embodiments of an apparatus and method forestimating bio-information will be described in detail with reference tothe accompanying drawings. Various example embodiments of the apparatusfor estimating bio-information may be mounted in terminals, such as asmartphone, a tablet personal computer (PC), a desktop computer, alaptop computer, etc., wearable devices, and the like. In this case,examples of the wearable devices may include a wristwatch-type wearabledevice, a bracelet-type wearable device, a wristband-type wearabledevice, a ring-type wearable device, a glasses-type wearable device, aheadband-type wearable device, etc., but the wearable devices are notlimited thereto.

FIG. 1 is a block diagram illustrating an apparatus for estimatingbio-information according to an example embodiment.

Referring to FIG. 1, the apparatus 100 for estimating bio-informationincludes a sensor part 110 and a processor 120.

The sensor part 110 includes a pixel array having a plurality of pixels.Each pixel may include one or more light sources for emitting light ontoan object, and one or more detectors for detecting light scattered orreflected from the object. Further, a partition wall for blocking lightmay be disposed between the pixels and/or between the light source andthe detector of each pixel.

The light source may include a light emitting diode (LED), a laser diode(LD), a phosphor, and the like. If each pixel includes a plurality oflight sources, the light sources may emit light of differentwavelengths. The detector may detect light returning after the light,emitted by the light source, is absorbed into or reflected or scatteredfrom the object OBJ. The detector may include a photodiode, a phototransistor (PTr), an image sensor, and the like.

In addition, the sensor part 110 may further include a fingerprintsensor. The fingerprint sensor may be disposed at the top or bottom ofthe pixel array of the sensor part 110. The fingerprint sensor mayacquire an image of wrinkles on a body part being in contact with thepixel array. However, the wrinkle image is not limited thereto, and maybe acquired by manufacturing each pixel of the pixel array in asufficiently small size and by scan driving all of the pixels in thepixel array. Here, the body part may be any part of the body in which aphotoplethysmography (PPG) signal may be detected therefrom, and thefollowing description will be given using a finger as an example of thebody part, such that wrinkles on the body part may be specified as afingerprint, and a “fingerprint center point,” described in relation tothe fingerprint, may be an example of a characteristic point of wrinkleson a body part.

The processor 120 may be electrically connected to the sensor part 110,and may control the sensor part 110 in response to a request forestimating bio-information. Further, the processor 120 may receive alight signal from the sensor part 110, and may estimate bio-informationbased on the received light signal. In this case, the bio-informationmay include triglyceride, body fat percentage, body water, bloodglucose, cholesterol, carotenoid, protein, uric acid, and the like, butis not limited thereto. The following description will be given usingtriglyceride as an example.

For example, in response to a request for estimating bio-information,the processor 120 may drive the sensor part 110 based on a first sensorconfiguration. In this case, the first sensor configuration may includeinformation, such as a driving method, a driving order, a light sourceintensity, a duration, etc., of the sensor part 110. In addition, theprocessor 120 may obtain contact information of the object based on thelight signal obtained by the sensor part 110 based on the first sensorconfiguration. In this case, the contact information may include acontact area of the object, a center point of the contact area, afingerprint center point, a contact direction, etc., but is not limitedthereto.

Based on obtaining the contact information as described above, theprocessor 120 may determine a second sensor configuration, and may drivethe sensor part 110 based on the determined second sensor configuration.The second sensor configuration may be determined to include variouscombinations of light source pixels having light sources to be drivenand detector pixels having detectors to be driven among all of thepixels of the sensor part 110, with the light sources and the detectorsbeing disposed at different distances from each other so that scatteredlight signals may be obtained via two or more different paths. Forexample, the combinations of pixels may include a combination of onelight source pixel and a plurality of detector pixels, a combination ofa plurality of light source pixels and one detector pixel, a combinationof a plurality of light source pixels and a plurality of detectorpixels, and the like. In this case, the light source pixels may refer topixels having light sources to be driven, and the detector pixels mayrefer to pixels having detectors to be driven, in the array of thepixels.

In addition, based on the sensor part 110 obtaining the light signalbased on the second sensor configuration, the processor 120 may estimatebio-information based on the obtained light signal. The processor 120may amplify the light signal obtained by the sensor part 110 by using anamplifier, or may convert the signal into a digital signal by using ananalog-digital converter, and the like.

FIG. 2 is a block diagram illustrating an apparatus for estimatingbio-information according to another example embodiment.

Referring to FIG. 2, the apparatus 200 for estimating bio-informationaccording to another example embodiment includes the sensor part 110,the processor 120, a storage 210, an output interface 220, and acommunication interface 230. The sensor part 110 and the processor 120are described above.

The storage 210 may store information related to estimatingbio-information. For example, the storage 210 may store a light signaland/or an estimated bio-information value. Further, the storage 210 maystore a first sensor configuration, a reference sensor configuration, asecond sensor configuration, criteria for determining the second sensorconfiguration, criteria for obtaining contact information, usercharacteristic information, and the like. In this case, the usercharacteristic information may include a user's age, gender, healthcondition, and the like.

The storage 210 may include at least one storage medium of a flashmemory type memory, a hard disk type memory, a multimedia card microtype memory, a card type memory (e.g., a secure digital (SD) memory, aneXtreme digital (XD) memory, etc.), a Random Access Memory (RAM), aStatic Random Access Memory (SRAM), a Read Only Memory (ROM), anElectrically Erasable Programmable Read Only Memory (EEPROM), aProgrammable Read Only Memory (PROM), a magnetic memory, a magneticdisk, and an optical disk, and the like, but is not limited thereto.

The output interface 220 may provide processing results of the processor120 for a user. For example, the output interface 220 may display anestimated bio-information value on a display. In this case, if theestimated bio-information value falls outside of a normal range, theoutput interface 220 may provide a user with warning information bychanging color, line thickness, etc., or displaying the abnormal valuealong with a normal range, so that the user may easily recognize theabnormal value. Further, along with or without the visual display, theoutput interface 220 may provide a bio-information estimation result ina non-visual manner such as by voice, vibrations, tactile sensation, andthe like, using a voice output module such as a speaker, or a hapticmodule, and the like.

The communication interface 230 may communicate with an external deviceto transmit and receive various data related to estimatingbio-information. In this case, the external device may include aninformation processing device such as a smartphone, a tablet PC, adesktop computer, a laptop computer, and the like. For example, thecommunication interface 230 may transmit a bio-information estimationresult to a user's smartphone, and the like, so that the user may manageand monitor the bio-information estimation result by using a devicehaving a relatively high performance.

In this case, the communication interface 230 may communicate with theexternal device by using various wired or wireless communicationtechniques, such as Bluetooth communication, Bluetooth Low Energy (BLE)communication, Near Field Communication (NFC), wireless local areanetwork (WLAN) communication, Zigbee communication, Infrared DataAssociation (IrDA) communication, wireless fidelity (Wi-Fi) Direct (WFD)communication, Ultra-Wideband (UWB) communication, Ant+ communication,Wi-Fi communication, Radio Frequency Identification (RFID)communication, 3G communication, 4G communication, 5G communication, andthe like. However, is the foregoing communication techniques areexamples, and are not intended to be limiting.

FIG. 3 is a block diagram illustrating a configuration of a processoraccording to an example embodiment. FIGS. 4A and 4B are diagramsexplaining an example of obtaining contact information of an object.FIGS. 4C, 4D, and 4E are diagrams explaining an example of obtaining asecond sensor configuration. FIGS. 5A and 5B are diagrams explaining anexample of estimating bio-information.

Referring to FIG. 3, a processor 300 according to an embodiment includesa sensor driver 310, a contact information obtainer 320, a sensorconfiguration determiner 330, and an estimator 340.

Referring to FIG. 4A, the sensor part 110 may include a pixel array 40having a plurality of pixels 41. Each pixel 41 may include one or morelight sources L1 and L2 and a detector PD. In this case, a partitionwall 42 may be disposed between the pixels 41 and/or between the lightsources L1 and L2 and the detector PD of each pixel 41.

The sensor driver 310 may drive the pixel array 40 by referring to thefirst sensor configuration for obtaining contact information of a fingerwhen the finger is placed on the sensor part 110. The first sensorconfiguration may include pixels 41 to be driven such as information onpixels to be driven for obtaining contact information in the entirepixel array 40. In this case, the pixels 41 to be driven may be set toall of the pixels 41 in the pixel array 40. However, the pixels 41 to bedriven are not limited thereto; and by considering power consumption,required accuracy of estimation, and the like, the pixels 41 to bedriven may be set to pixels 41 in some of the rows/columns such as, forexample, pixels 41 in odd number/even number rows/columns. Further, thefirst sensor configuration may include a driving method, a drivingorder, a light source intensity, a duration, and the like. The drivingmethod may be set to any one of, for example, sequential driving,time-division driving, and simultaneous driving.

By driving all the pixels 41 to be driven under the control of thesensor driver 310 by turning on the light sources of a specific drivenpixel 41 and detecting light using the detector of the specific drivenpixel 41, the sensor part 110 may scan a finger and may obtain lightsignals for all the driven pixels 41.

Referring to FIG. 4B, when the finger OBJ comes into contact with thepixel array 40 of the sensor part 110, the pixel array 40 of the sensorpart 110 may be divided into a contact area (CA) that is in contact withthe finger OBJ, and a non-contact area (NA) that is not in contact withthe finger OBJ.

Based on the sensor part 110 obtaining the light signals by scanning thefinger, the contact information obtainer 320 may obtain contactinformation of the finger based on the obtained light signals, asillustrated in FIG. 4B. For example, the contact information obtainer320 may obtain, as the contact area CA, an area of pixels in which anamount of light received by the respective pixels is greater than orequal to a predetermined threshold value. Alternatively, the contactinformation obtainer 320 may obtain, as the contact area CA, an area ofpixels in which an amount of light is greater than or equal to apredetermined percentage of an average value of total amounts of lightreceived by the respective pixels, an area of pixels in which an amountof light is greater than or equal to a predetermined percentage of amaximum amount of light, or an area of pixels in which an amount oflight is greater than or equal to a predetermined percentage of anaverage value of amounts of light falling within a predetermined rangeof the maximum amount of light. However, these are merely examples.Further, the contact information obtainer 320 may obtain a center pointof the obtained contact area CA and/or a contact direction.

In addition, if the sensor part 110 obtains a fingerprint image, thecontact information obtainer 320 may analyze the fingerprint image toobtain a fingerprint center point, a contact area and/or a contactdirection.

The sensor configuration determiner 330 may determine a second sensorconfiguration for estimating bio-information based on the contactinformation. In this case, the second sensor configuration may includelight source pixels having light sources to be driven for emitting lightonto the object, and detector pixels having detectors to be driven fordetecting light signals from the object. In this case, the light sourcepixels may be different from the detector pixels. The light source pixelmay include at least one pixel 41, and the detector pixel may include aplurality of pixels 41 for detecting light scattered from differentpositions of the object.

Referring to FIG. 4C, the sensor configuration determiner 330 maydetermine a pixel 11, located at a predetermined position in a contactdirection D, to be a light source pixel LP among the pixels of the pixelarray 40 in a contact area CA. In this case, criteria for determiningthe light source pixel such as, for example, determining a pixel locatedat the foremost of the contact area CA, may be preset.

Further, the sensor configuration determiner 330 may determine, as adetector pixel DP, pixels 9, 10, 14, 15, 16, 17, 19, 20, 21, 22, 23, 27,and 28 located within a predetermined range from the center point C ofthe contact area. In this case, criteria for determining the detectorpixel DP such as, for example, a predetermined range, a shape (e.g.,circle, oval, polygon, etc.) of the predetermined range, and the like,may be preset. However, the criteria are not limited thereto, and thedetector pixel PD may be defined as various pixels, such as all thepixels, all the pixels except the light source pixels LP, or all thepixels located below the light source pixels LP, and the like.

Referring to FIG. 4D, the sensor configuration determiner 330 maydetermine a light source pixel and a detector pixel of the second sensorconfiguration based on a pre-defined reference sensor configuration. Forexample, the reference sensor configuration may include a light sourcepixel LP1, a detector pixel DP1, and/or information on a referencecenter point in a reference area of the pixel array 40. In this case,the reference area may be, for example, the entire area of the pixelarray 40, and the reference center point may be a center point of thepixel array 40, but is not limited thereto.

Based on the contact information obtainer 320 obtaining the contactarea, the contact direction, and the center point of the contact area,the sensor configuration determiner 330 may map the reference centerpoint to the center point of the contact area, and may turn thereference direction to the right in the contact direction D, to map thereference area to the contact area CA so that the reference area mayoverlap the contact area CA. Based on the mapping, the sensorconfiguration determiner 330 may determine the pixel 11, correspondingto the light source pixel LP1, and pixels 7, 8, 13, 14, 15, 19, 20, 21,22, 25, 26, 27, 28, 29, 31, 32, 33, 34, and 35, corresponding to thedetector pixel DP1, of the reference sensor configuration to be a lightsource pixel LP2 and a detector pixel DP2, respectively, of the secondsensor configuration. However, this is merely an example.

FIG. 4E illustrates examples of determining the second sensorconfiguration based on the fingerprint image. As illustrated in FIG. 4E,the sensor configuration determiner 330 may adaptively determine thelight source pixels LP1 and LP2 and the detector pixels DP1 and DP2based on the fingerprint area, fingerprint direction, and fingerprintcenter points C1 and C2. In this case, if a fingerprint center point isnot located within a predetermined range of the sensor part 110, thesensor configuration determiner 330 may guide a user to place the fingeron the sensor part 110 again. In this case, the predetermined range maybe preset.

As described above, according to the example embodiments of the presentdisclosure, even when the contact area and/or the contact direction ofthe finger are changed, the light source pixels and the detector pixelsof the second sensor configuration may be determined adaptively, suchthat light signals may be detected at a predetermined position of thefinger or at an actual contact position of the finger, thereby improvingaccuracy in estimating bio-information.

Based on the sensor configuration determiner 330 determining the secondsensor configuration, the sensor driver 310 may drive the light sourcepixels and the detector pixels of the sensor part 110 based on thesecond sensor configuration.

Based on the sensor part 110 obtaining a plurality of light signals of aplurality of light paths based on the second sensor configuration, theestimator 340 may estimate bio-information based on the obtainedplurality of light signals. FIG. 5A illustrates an example of a map oflight intensity for each distance when a plurality of detector pixelsare located at different distances from the light source pixels.

The estimator 340 may estimate bio-information based on the plurality oflight signals obtained at different distances. For example, theestimator 340 may calculate a scattering coefficient by using the lightsignals obtained at each distance, and may estimate bio-information byusing the calculated scattering coefficient. In this case, thescattering coefficient indicates a decrease in light intensity due toscattering of light when light emitted by the light source travels aunit length, and may be defined as, for example, a ratio of intensitiesof scattered light signals detected by a plurality of detectors or avalue proportional to the ratio. Further, the scattering coefficient maybe calculated by considering distances of the respective detectors fromthe light sources. Alternatively, the estimator 340 may calculate ascattering coefficient by obtaining a representative value of theplurality of light signal intensities. In this case, the representativevalue of the plurality of light signal intensities may be calculatedbased on various criteria, such as a maximum signal intensity value, amean value or a median value of the signal intensities, and the like.

For example, when calculating the scattering coefficient by using onescattered light signal detected by one detector, the estimator 340 maycalculate the scattering coefficient by using, for example, thefollowing Equations 1 and 2.

$\begin{matrix}{{\ln\left\{ {\rho^{2}\frac{R(\rho)}{S_{0}}} \right\}} = {{{- \mu_{eff}}\rho} + {\ln\frac{3\mu_{\alpha}}{2{\pi\mu}_{eff}}}}} & \left\lbrack {{Equation}\mspace{14mu} 1} \right\rbrack \\{{\ln\left\{ {\rho^{3}\frac{R(\rho)}{S_{0}}} \right\}} = {{{- \mu_{eff}}\rho} + {\ln\frac{1}{2{\pi\mu}_{x}^{*}}}}} & \left\lbrack {{Equation}\mspace{14mu} 2} \right\rbrack\end{matrix}$

Herein, R(ρ) denotes the intensity of light detected by a detectorlocated at a distance of ρ from the light source; p denotes the distancebetween the light source and the detector; μ_(a) denotes an absorptioncoefficient; ρ_(eff) denotes an effective attenuation coefficient; S₀denotes the intensity of light emitted by the light source; and μ_(s)denotes the scattering coefficient.

In yet another example, when calculating the scattering coefficient byusing two signals of scattered light detected by two detectors disposedat different distances after the light emitted by the light source, theestimator 340 may calculate the scattering coefficient by using thefollowing Equation 3.

$\begin{matrix}{\mu_{x}^{*} = {\frac{1}{3\mu_{\alpha}}\left\{ {\frac{1}{\rho_{2} - \rho_{1}}\ln\;\frac{\rho_{1}^{2}{R\left( \rho_{1} \right)}}{\rho_{2}^{2}{R\left( \rho_{2} \right)}}} \right\}^{2}}} & \left\lbrack {{Equation}\mspace{14mu} 3} \right\rbrack\end{matrix}$

Herein, ρ₁ denotes a distance between the light source and a firstdetector; ρ₂ denotes a distance between the light source and a seconddetector; R(ρ₁) denotes the intensity of light detected by the firstdetector; R(ρ₂) denotes the intensity of light detected by the seconddetector; and μ_(s) denotes the scattering coefficient. The equation forcalculating the scattering coefficient may be defined differentlyaccording to the number of detectors detecting light emitted by thelight source.

Based on the plurality of detectors obtaining the plurality of scatteredlight signals, the estimator 340 may select some of the obtained lightsignals, and may calculate the scattering coefficient by using theselected light signals. For example, the estimator 340 may calculate asimilarity between the plurality of scattered light signals, and mayselect light signals having a calculated similarity greater than orequal to a first threshold value. Alternatively, the estimator 340 maycalculate a similarity between the plurality of scattered light signals,and may calculate the scattering coefficient by using light signalswhich remain after excluding light signals having a calculatedsimilarity less than or equal to a second threshold value. In this case,the similarity may include at least one of Euclidean distance, Pearsoncorrelation coefficient, Spearman correlation coefficient, and Cosinesimilarity.

Based on calculating the scattering coefficient, the estimator 340 mayobtain a triglyceride value by using an estimation model which defines acorrelation between the scattering coefficient and bio-information suchas triglycerides. In this case, the estimation model may be expressed inthe form of linear/non-linear functions or a matching table indicating acorrelation between the scattering coefficient and a bio-informationestimation value. FIG. 5B illustrates a correlation between a value ofthe left side of the above Equation 1 and a distance according to achange in triglyceride levels. As illustrated in FIG. 5B, as a bloodtriglyceride concentration changes, a scattering coefficient of bloodalso changes, such that a scattered light signal may change withdistance between the light source and the detector. As described above,an estimation model may be pre-defined by using the correlation betweenthe scattering coefficient and the triglyceride concentration.

FIG. 6 is a flowchart illustrating a method of estimatingbio-information according to an example embodiment. The method of FIG. 6is an example of a method of estimating bio-information which isperformed by the apparatuses 100 and 200 for estimating bio-informationaccording to the example embodiments of FIG. 1 or 2.

Referring to FIG. 6, in response to a request for estimatingbio-information, the apparatus for estimating bio-information may drivea sensor part based on a first sensor configuration to detect ascattered light signal from an object in operation 610. In this case,the apparatus for estimating bio-information may control driving of thesensor part based on a pre-defined first sensor configuration. In thiscase, if the sensor part includes a fingerprint sensor, the apparatusfor estimating bio-information may obtain a fingerprint image.

Then, the apparatus for estimating bio-information may obtain contactinformation in operation 620 based on the amount of light received byeach pixel, which is obtained by scanning the object, being in contactwith the sensor part, based on the first sensor configuration, and/orthe fingerprint image. In this case, the contact information may includea contact area, a center point of the contact area, a fingerprint centerpoint, a contact direction, and the like.

Subsequently, the apparatus for estimating bio-information may determinea second sensor configuration based on the obtained contact informationin operation 630. In this case, the second sensor configuration mayinclude information on light source pixels and detector pixels, disposedat different distances from the light source pixels, so that scatteredlight signals may be obtained at various positions spaced apart bydifferent distances from the light sources.

For example, the apparatus for estimating bio-information may determineone or more pixels, located at predetermined positions in a contactdirection, to be light source pixels of the second sensor configuration,among pixels in a contact area; and may determine all pixels or pixels,located within a predetermined range from the center point of thecontact area or the fingerprint center point, to be detector pixels ofthe second sensor configuration.

In another example, the apparatus for estimating bio-information may mapa reference area, a reference direction, and a reference center point ofthe pre-defined reference sensor configuration to the contact area, thecontact direction, and the center point of the contact area. Based onthe mapping, the apparatus for estimating bio-information may determinepixels, corresponding to light source pixels, and pixels correspondingto detector pixels, of the reference sensor configuration to be thelight source pixels and the detector pixels, respectively, of the secondsensor configuration.

Next, the apparatus for estimating bio-information may detect aplurality of scattered light signals by driving the sensor part based onthe second sensor configuration in operation 640.

Then, the apparatus for estimating bio-information may estimatebio-information based on the light signals obtained according to thesecond sensor configuration in operation 650. For example, the apparatusfor estimating bio-information may calculate a scattering coefficientbased on the light signals, and may estimate bio-information by using apre-defined estimation model. In this case, if a plurality of lightsignals are obtained, the apparatus for estimating bio-information maycalculate a similarity between the light signals, and may calculate thescattering coefficient by using only the light signals having thecalculated similarity greater than or equal to a first threshold value.Alternatively, the apparatus for estimating bio-information maycalculate the scattering coefficient by using light signals which remainafter excluding light signals having the calculated similarity less thanor equal to a second threshold value.

FIG. 7 is a diagram illustrating an example of a wearable device. Theaforementioned example embodiments of the apparatuses 100 and 200 forestimating bio-information may be mounted in the wearable device.

Referring to FIG. 7, the wearable device 700 includes a main body 710and a strap 730.

The strap 730, which is connected to both ends of the main body 710, maybe flexible so as to be wrapped around a user's wrist. The strap 730 maybe composed of a first strap and a second strap which are separated fromeach other. Respective ends of the first strap and the second strap areconnected to the main body 710, and the other ends thereof may beconnected to each other via a connecting means. In this case, theconnecting means may be formed as magnetic connection, Velcroconnection, pin connection, and the like, but is not limited thereto.Further, the strap 730 is not limited thereto, and may be integrallyformed as a non-detachable band.

In this case, air may be injected into the strap 730, or the strap 730may be provided with an air bladder to have elasticity according to achange in pressure applied to the wrist, and may transmit the change inpressure of the wrist to the main body 710.

A battery may be embedded in the main body 710 or the strap 730 tosupply power to the wearable device 700.

The main body 710 may include a sensor part 720 mounted on one sidethereof. The sensor part 720 may include a pixel array having pixels,each of which includes a light source and a detector. In addition, thesensor part 720 may further include a fingerprint sensor for obtaining afingerprint image when the finger comes into contact with the sensorpail 720.

A processor may be mounted in the main body 710. The processor may beelectrically connected to modules mounted in the wearable device 700.The processor may estimate bio-information based on light signalsobtained by the sensor part 720. In this case, by controlling the sensorpart 720 based on a first sensor configuration, the processor may scanthe object and may obtain contact information of the object. Further,the processor may determine a second sensor configuration based on thecontact information, and may control the sensor part 720 based on thedetermined second sensor configuration. As described above, based onobtaining the light signals based on the second sensor configuration,the processor may obtain bio-information by calculating a scatteringcoefficient based on the obtained light signals.

Further, the main body 710 may include a storage which stores referenceinformation for estimating bio-information and information processed byvarious modules thereof.

In addition, the main body 710 may include a manipulator 740 which isprovided on one side surface of the main body 710, and receives a user'scontrol command and transmits the received control command to theprocessor. The manipulator 740 may have a power button to input acommand to turn on/off the wearable device 700.

Further, a display for outputting information to a user may be mountedon a front surface of the main body 710. The display may have a touchscreen for receiving touch input. The display may receive a user's touchinput and transmit the touch input to the processor, and may displayprocessing results of the processor.

Moreover, the main body 710 may include a communication interface forcommunication with an external device. The communication interface maytransmit a bio-information estimation result to the external device suchas a user's smartphone.

FIG. 8 is a diagram illustrating an example of a smart device. In thiscase, the smart device may include a smartphone, a tablet PC, and thelike. The smart device may include functions of the aforementionedexample embodiments of the apparatuses 100 and 200 for estimatingbio-information.

Referring to FIG. 8, the smart device 800 includes a main body 810 and asensor part 830 mounted on one surface of the main body 810. Forexample, the sensor part 830 may further include a fingerprint sensor.

Moreover, a display may be mounted on a front surface of the main body810. The display may visually output a bio-information estimationresult, a health condition evaluation result, and the like. The displaymay include a touch screen, and may receive information input throughthe touch screen and transmit the information to a processor.

The main body 810 may include an image sensor 820 as illustrated in FIG.8. The image sensor 820 may capture various images, and may acquire, forexample, a fingerprint image of a finger being in contact with thesensor part 830.

The processor may be mounted in the main body 810 to be electricallyconnected to various modules thereof, and may control operations of themodules. The processor may control the sensor part based on a firstsensor configuration for obtaining contact information, and may obtaincontact information based on light signals obtained according to thefirst sensor configuration. In addition, the processor may adaptivelydetermine a second sensor configuration based on the contactinformation, and may control the sensor part according to the determinedsecond sensor configuration. In this manner, the processor may obtainlight signals at contact positions of the object, thereby improvingaccuracy in estimating bio-information.

The example embodiments may be implemented by computer-readable codewritten on a non-transitory computer-readable medium and executed by aprocessor. The non-transitory computer-readable medium may be any typeof recording device in which data is stored in a computer-readablemanner.

Examples of the computer-readable medium include a ROM, a RAM, a CD-ROMa magnetic tape, a floppy disc, an optical data storage, and a carrierwave (e.g., data transmission through the Internet). The non-transitorycomputer-readable medium can be distributed over a plurality of computersystems connected to a network so that computer-readable code is writtenthereto and executed therefrom in a decentralized manner. Functionalprograms, code, and code segments for implementing the exampleembodiments can be readily deduced by programmers of ordinary skill inthe art to which the present disclosure pertains.

The present disclosure has been described herein with regard to exampleembodiments. However, it will be obvious to those skilled in the artthat various changes and modifications can be made without changingtechnical conception and features of the present disclosure. Thus, it isclear that the above-described example embodiments are illustrative inall aspects and are not intended to limit the present disclosure.

What is claimed is:
 1. An apparatus for estimating bio-information, theapparatus comprising: a sensor part including a pixel array of pixels,each pixel including a light source and a detector; and a processorconfigured to: based on an object being in contact with the sensor part,drive the sensor part based on a first sensor configuration; obtaincontact information of the object based on an amount of light receivedby each pixel according to the first sensor configuration; determine asecond sensor configuration based on the contact information; drive thesensor part based on the second sensor configuration; and estimate thebio-information based on light signals obtained according to the secondsensor configuration.
 2. The apparatus of claim 1, wherein the firstsensor configuration comprises at least one of a time-division drivingmethod, a sequential driving method, a simultaneous driving method, adriving order, a light source intensity, and a duration.
 3. Theapparatus of claim 1, wherein the processor is further configured to:obtain the contact information based on at least one of a pixel havingan amount of light being greater than or equal to a predeterminedthreshold value, a pixel having an amount of light being greater than orequal to a predetermined percentage of an average value of a totalamount of light, a pixel having an amount of light being greater than orequal to a predetermined percentage of a maximum amount of light, and apixel having an amount of light being greater than or equal to apredetermined percentage of an average value of an amount of lightfalling within a predetermined range of the maximum amount of light. 4.The apparatus of claim 1, wherein the processor is further configured toobtain the contact information including at least one of a contact areaof the object, a center point of the contact area, a fingerprint centerpoint, and a contact direction.
 5. The apparatus of claim 4, wherein theprocessor is further configured to, based on the contact information,determine a light source pixel and a detector pixel of the second sensorconfiguration.
 6. The apparatus of claim 5, wherein the processor isfurther configured to: determine one or more pixels, located atpredetermined positions in the contact direction, to be light sourcepixels of the second sensor configuration, among pixels in the contactarea; and determine one or more pixels, located within a predeterminedrange from the center point of the contact area or the fingerprintcenter point, to be detector pixels of the second sensor configuration.7. The apparatus of claim 5, wherein the processor is further configuredto: map a reference area, a reference direction, and a reference centerpoint of a pre-defined reference sensor configuration to the contactarea, the contact direction, and the center point of the contact area;and based on the mapping, determine pixels corresponding to light sourcepixels of the pre-defined reference sensor configuration to be the lightsource pixels of the second sensor configuration, and pixelscorresponding to detector pixels of the pre-defined reference sensorconfiguration to be detector pixels of the second sensor configuration.8. The apparatus of claim 4, wherein the sensor part is configured toobtain a fingerprint image based on the object being in contact with thesensor part, and wherein the processor is further configured to obtainthe contact information based on the fingerprint image.
 9. The apparatusof claim 8, wherein the processor is further configured to, based on thefingerprint center point not being located within a predetermined rangeof the sensor part, control an output interface to guide a user to placethe object on the sensor part.
 10. The apparatus of claim 1, wherein theprocessor is further configured to: determine a scattering coefficientbased on the light signals obtained according to the second sensorconfiguration; and estimate the bio-information based on the scatteringcoefficient.
 11. The apparatus of claim 1, wherein the processor isfurther configured to: based on the light signals being obtainedaccording to the second sensor configuration, determine a similaritybetween the light signals; and select light signals, having thesimilarity being greater than or equal to a first threshold value, aslight signals for estimating the bio-information.
 12. The apparatus ofclaim 1, wherein the processor is further configured to: based on thelight signals being obtained according to the second sensorconfiguration, determine a similarity between the light signals; andexclude light signals, having the similarity being less than or equal toa second threshold value, as light signals for estimating thebio-information.
 13. The apparatus of claim 10, wherein thebio-information comprises at least one of triglyceride, body fatpercentage, body water, blood glucose, cholesterol, carotenoid, protein,and uric acid.
 14. A method of estimating bio-information, the methodcomprising: based on an object being in contact with a sensor part,driving the sensor part based on a first sensor configuration; obtainingcontact information of the object based on an amount of light receivedby each pixel of the sensor part according to the first sensorconfiguration; determining a second sensor configuration based on thecontact information; driving the sensor part based on the second sensorconfiguration; and estimating the bio-information based on light signalsobtained according to the second sensor configuration.
 15. The method ofclaim 14, wherein the obtaining the contact information comprisesobtaining the contact information based on at least one of a pixelhaving an amount of light being greater than or equal to a predeterminedthreshold value, a pixel having an amount of light being greater than orequal to a predetermined percentage of an average value of a totalamount of light, a pixel having an amount of light being greater than orequal to a predetermined percentage of a maximum amount of light, and apixel having an amount of light being greater than or equal to apredetermined percentage of an average value of an amount of lightfalling within a predetermined range of the maximum amount of light. 16.The method of claim 14, wherein the obtaining the contact informationcomprises obtaining the contact information including at least one of acontact area of the object, a center point of the contact area, afingerprint center point, and a contact direction.
 17. The method ofclaim 16, wherein the determining the second sensor configurationcomprises determining, based on the contact information, a light sourcepixel and a detector pixel of the second sensor configuration.
 18. Themethod of claim 17, wherein the determining the second sensorconfiguration comprises: determining one or more pixels, located atpredetermined positions in the contact direction, to be light sourcepixels of the second sensor configuration, among pixels in the contactarea; and determining one or more pixels, located within a predeterminedrange from the center point of the contact area or the fingerprintcenter point, to be detector pixels of the second sensor configuration.19. The method of claim 17, wherein the determining the second sensorconfiguration comprises: mapping a reference area, a referencedirection, and a reference center point of a pre-defined referencesensor configuration to the contact area, the contact direction, and thecenter point of the contact area; and based on the mapping, determiningpixels corresponding to light source pixels of the pre-defined referencesensor configuration to be the light source pixels of the second sensorconfiguration, and pixels corresponding to detector pixels of thepre-defined reference sensor configuration to be the detector pixels ofthe second sensor configuration.
 20. The method of claim 17, furthercomprising: obtaining a fingerprint image based on the object being incontact with the sensor part, wherein the obtaining the contactinformation comprises obtaining the contact information based on thefingerprint image.
 21. The method of claim 20, further comprising, basedon the fingerprint center point not being located within a predeterminedrange of the sensor part, controlling an output interface to guide auser to place the object on the sensor part.
 22. The method of claim 14,wherein the estimating the bio-information comprises: determining ascattering coefficient based on two or more light signals obtained bythe sensor part; and estimating the bio-information based on thescattering coefficient.
 23. The method of claim 14, wherein theestimating the bio-information comprises: based on the light signalsbeing obtained by the sensor part, determining a similarity between thelight signals; and selecting light signals, having the similarity beinggreater than or equal to a first threshold value, as light signals forestimating the bio-information.
 24. The method of claim 14, wherein theestimating the bio-information comprises: based on the light signalsbeing obtained by the sensor part, determining a similarity between thelight signals; and excluding light signals, having the similarity beingless than or equal to a second threshold value, as light signals forestimating the bio-information.
 25. A method of estimatingbio-information of a user, the method comprising: driving a first lightsource pixel and a first set of detector pixels of a pixel array of asensor, based on a first sensor configuration; identifying a contactarea of the pixel array that is contact with an object of the user,based on driving the first light source pixel and the first set ofdetector pixels; identifying a second sensor configuration based on thecontact area; driving a second light source pixel and a second set ofdetector pixels of the pixel array of the sensor, based on the secondsensor configuration; and obtaining light signals based on driving thesecond light source pixel and the second set of detector pixels; andestimating the bio-information of the user based on the light signals.